Recent genome wide association studies have led to the reliable identification of multiple common SNPs associated with increased incidence of a number of common human diseases. These results offer the tantalizing prospect of major new insights into the nature of complex trait disease in general and specific understanding of the mechanisms underlying major common human diseases. Deriving maximum insight is not trivial, and requires the development and application of a range of computational and experimental techniques. The goal of this project is to develop and apply such methods to the currently available association studies and new results that will be available shortly. The project focuses on the gene and gene product level contributions to common human disease. These processes constitute a key part of the multiple level mechanisms by which SNPs influence disease risk, and a full understanding of their contributions is essential to effective investigation of higher level pathway and subsystems impact. We take a two pronged approach. First, computational methods will be used to identify a set of possible candidate SNPs in established susceptibility loci for common diseases. For each of these SNPs, a set of possible mechanisms of action is examined. Specifically, effects on gene expression level;messenger RNA structure;processing;stability and splicing;and on protein folding, structure, stability and function in vivo. Secondly, for one of the mechanisms that it is already clear plays a significant role, missense SNPs in proteins, we will experimentally investigate the impact of the resulting amino acid substitutions on in vitro function. To this end, we will clone, express and purify a number of affected proteins and the SNP variants, and investigate their properties, particularly structural stability and interaction with appropriate binding partners. Initial studies are on the large scale WTCCC genome wide association data for common diseases, and on additional association data for Crohn's disease. As more data become available, the computational analysis will be extended to include additional association studies as well as re-sequencing data. The outcome will be a comprehensive computational analysis of the mechanisms by which SNPs influence disease susceptibility at the gene and protein level, and in high priority cases, extensive experimental characterization of the impact of relevant missense SNPs on protein function. All data will be made available in downloadable form, as well as through an interactive web interface. In addition, we will develop an annotation and discussion facility, so that the results can be maximally exploited. PUBLIC HEALTH RELEVANCE: New data are for the first time reliably establishing many associations between genetic variation among individuals and susceptibility to a number of common human diseases. These data open the way for investigation of the mechanisms underlying disease and hence the development of new therapies. We will use computational and experimental methods to determine the genome and protein level mechanisms, making use of these new data.